National Park Visitor Spending and Payroll Impacts 2006

National Park Visitor Spending and Payroll Impacts 2006 Daniel J. Stynes Michigan State University National Park Service Social Science Program October 2007 Department of Community, Agriculture, Recreation and Resource Studies Michigan State University

National Park Visitor Spending and Payroll Impacts, 2006 Daniel J. Stynes October 2007 This report provides updated estimates of NPS visitor spending for 2006 and estimates the economic impacts of visitor spending and the NPS payroll on local economies. Visitor spending and impacts are estimated using the MGM2 model (Stynes et. al., 2000) based on calendar year 2006 park visits, spending averages from park visitor surveys, and local area economic multipliers. Impacts of the NPS payroll are estimated based on fiscal year 2006 payroll data for each park. Visitor spending impacts are estimated for all park units with visitation data. Payroll impacts are estimated for all parks including administrative units and parks without visit count data. Impacts measure the direct and secondary effects of visitor spending and park payrolls on local economies in terms of jobs, income and value added 1. Impacts of construction activity and park purchases of goods and services from local firms are not included. Local regions are defined as a 50 mile radius 2 around each park. Direct effects cover businesses selling goods and services directly to park visitors. Secondary effects include indirect and induced effects resulting from sales to backward linked industries within the local region and household spending of income earned directly or indirectly from visitor spending. Sales in retail and wholesale trade sectors represent the margins accruing to local firms on goods sold to park visitors. Systemwide totals are estimated by summing the spending and impact estimates for all park units. Results for individual park units are reported in the Appendix. Visitor Spending The National Park System received 273 million recreation visits in 2006. Visitor spending was estimated by dividing visitors to each park into segments with distinct spending patterns and applying spending averages based on surveys of park visitors at selected parks. As spending averages are measured on a party day basis (party nights for overnight trips), the NPS counts of recreation visits are converted from person entries to a park to party days in the area by applying average party size, length of stay and park re- 1 Jobs include full time and part time jobs. Seasonal positions are adjusted to an annual basis. income covers wages and salaries, including income of sole proprietors and payroll benefits. Value added is the sum of personal income, profits and rents, and indirect business taxes. It can also be defined as total sales net of the costs of all non-labor inputs. Value added is the preferred economic measure of the contribution of an industry or activity to the economy. 2 The fifty mile radius is a general average representing the primary impact region around most parks. The radius is closer to 30 miles for parks in urban settings and can be as large as 100 miles for some western parks. Economic multipliers are based on regions defined as groupings of counties to approximate a 50 mile radius of the park. 1

entry factors. This adjusts for some double counting of visits. To the extent possible, spending not directly-related to a park visit is excluded 3. In 2006 there were 13.3 million recreation overnight stays in the parks representing 3% of all visits. Twenty-eight percent of park visits were day trips by local residents, 43% were day trips from 50 miles or more 4 and 29% involved an overnight stay near the park. Visitor spending depends on the number of days spent in the local area and also the type of lodging on overnight trips. Non-local day trips account for 36% of the party days spent in the local area, local day trips 27%, and overnight stays 37%. Twothirds of all overnight stays by park visitors are in motels, lodges or B&B s outside the park, another 21% are in campgrounds outside the park and twelve percent are inside the park in NPS campgrounds, lodges or backcountry sites. NPS Systemwide spending averages for 2006 are given in Table 1 for seven distinct visitor segments 5. A typical park visitor party on a day trip spends $39 if a local resident and $69 if non-local (Table 1). Spending averages do not include park entry fees. Table 1. National Park Visitor Spending in the Local Area by Segment, 2006 ($ per party per day/night) Visitor Segment Local Day Trip Non-local Day Trip Motel- In Camp- In Backcountry Motel- Out Camp- Out Spending category Motel, hotel cabin or B&B 0.00 0.00 154.43 0.00 7.86 100.95 0.00 Camping fees 0.00 0.00 0.00 18.79 3.49 0.00 22.58 Restaurants & bars 12.27 19.75 56.88 12.09 10.16 49.35 12.68 Amusements 4.37 9.23 19.67 7.75 6.02 16.66 14.68 Groceries 5.93 7.16 9.71 15.19 7.04 12.56 9.19 Gas & oil 7.40 17.88 21.81 19.26 16.99 16.93 16.83 Local transportation 0.51 1.23 3.33 1.20 0.75 2.58 1.05 Souvenirs 8.22 13.94 24.81 11.00 15.21 22.57 18.36 Total 38.70 69.19 290.64 85.29 67.51 221.59 95.37 On a party night basis, spending by visitors on overnight trips varies from $68 for backcountry campers to $291 for visitors staying in park lodges. Campers spend $95 per night if staying outside the park and $85 if staying inside the park. Spending averages at individual parks vary from these systemwide averages due to differences in local prices and spending opportunities. For example, while non-local visitors on day trips spent $32 3 For example, spending during extended stays in an area visiting relatives, on business, or when the park visit was not the primary trip purpose. For most historical sites and parks in urban areas spending for one day or night is counted for each park entry. Where several park units are within a 50 mile radius, adjustments are made for those visiting more than one park on the same day. 4 Day trips include pass thru visitors not spending a night within 50 miles of the park as well as stays with friends and relatives and in owned seasonal homes. 5 Systemwide spending averages are compiled from averages at individual parks based on the distribution of visitors by park and segment. It is not possible to provide error estimates for the systemwide averages as parks with visitor surveys do not constitute a statistical sample of all park visitors. Over 14,000 NPS visitors have provided spending information since 2000. See the methods section for details on estimates of spending averages for individual parks. 2

per party at Craters of the Moon NM, their counterparts at Grand Canyon spent $131. Visitors staying in park lodges spent over $500 per party per night at Grand Teton NP. In total, park visitors spent $10.73 billion in the local region surrounding the parks in 2006 6. Local residents account for 10% of this spending (Table 2). Visitors staying in motels and lodges outside the park account for over half of the total spending while non-local visitors on day trips contribute about a quarter of all spending. Over half of the visitor spending is for lodging and restaurant meals (Figure 1). Table 2. National Park Visitor Spending by Segment, 2006 Segment Total Spending $Millions Pct of Spending Local Day Trip $1,086 10% Non-local Day Trip $2,554 24% Lodge-In Park $333 3% Camp-In Park $240 2% Backcountry Campers $38 0% Motel-Outside Park $5,655 53% Camp-Outside Park $755 7% Other Overnight Visitors $68 1% Total $10,728 100% Souvenirs 14% Visitor Spending Lodging 28% Amusements 10% Auto/Local Transportation 16% Groceries 8% Restaurants 24% Figure 1. Distribution of National Park Visitor Spending 6 Spending figures exclude airfares and other trip spending beyond 50 miles of the park. Purchases of durable goods (boats, RV s) and major equipment are also excluded. Special expenses for commercial rafting trips, air overflights, and other special activities are not fully captured for all parks. 3

Impacts of Visitor Spending Economic impacts of visitor spending are estimated in the MGM2 model using multipliers for local areas around each park 7. Multipliers capture both the direct and secondary economic effects in gateway communities around the parks in terms of jobs, personal income, and value added. National totals are the sum of the local impacts for 355 park units that have counts of visitors. Both economic significance and economic impacts were estimated. The economic significance estimates in Table 3 measure the impacts of all visitor spending ($10.7 billion) including that of local visitors. Economic impacts in Table 4 exclude spending by local residents, estimating the impacts of the $9.6 billion spent by visitors who do not reside within the local region. Economic impact measures attempt to estimate the likely losses in economic activity to the region in the absence of the park 8. Should the park opportunities not be available, it is assumed that local residents would spend the money on other local activities, while visitors from outside the region would not have made a trip to the region. Local resident spending is included in the economic significance measures, as these capture all economic activity associated with park visits, including local and non-local visitors. Spending by local residents on visits to the park do not represent new money to the region and are therefore generally excluded when estimating impacts. To the extent possible, spending not directly associated with a park visit is also excluded in the impact estimates. For example, only one night s expenses are counted for visitors in the area primarily on business, visiting relatives, or visiting other attractions. For parks with visitor surveys, spending attributed to a park visit was estimated based on the percentage of visitors identifying the park visit as the primary purpose of the trip. Economic Significance The $10.7 billion spent by park visitors within 50 miles of the park (Table 2) has a total local economic effect (significance) of $13.0 billion in sales, $4.5 billion in personal income, and $7.0 billion in value added. Visitor spending supports about 213,000 jobs in gateway regions. Total effects may be divided between the direct effects that occur in businesses selling goods and services directly to park visitors and secondary effects that result from the circulation of this money within the local economy 9. 7 Sets of sector-specific multipliers in the MGM2 model were estimated with the IMPLAN system for four types of regions varying in population size and levels of economic development. A region type is assigned to each park based on surrounding populations. MGM2 multipliers are based on IMPLAN s Type II multipliers estimated with 2001 IMPLAN data for over 500 distinct regions. Job to sales ratios were adjusted to 2006 using the consumer price index. 8 The impact estimates do not take into account economic activity that might be generated by alternative uses of parks lands and facilities. Impacts represent reductions in local economic activity associated with the loss of visitor spending attributable to park visits. 9 Secondary effects include indirect effects of businesses buying goods and services from backward-linked local firms and induced effects of household spending of their earnings. 4

Direct effects are $8.7 billion in sales, $3.3 billion in personal income, $4.9 billion in value added and 173,000 jobs. The local region captures 80% of all visitor spending as direct sales. Note that direct sales of $8.7 billion is less than the $10.7 billion in visitor spending as the manufacturing share of most retail purchases (groceries, gas, sporting goods, souvenirs) immediately leaks out of the region to cover the cost of goods sold. Sales figures for retail and wholesale trade are the margins on these purchases. A small share of the manufacturing of these goods (producer prices) is assigned to local production. The average sales multiplier across all local park regions is 1.50, which means for every dollar of direct sales another $.50 in sales is generated in the region thru secondary effects. Table 3. Economic Significance of National Park Visitor Spending to Local Economies, 2006 Sales $Millions $Millions Value Added $Millions Sector/Spending category Jobs Direct Effects Motel, hotel cabin or B&B $2,780 54,389 $1,221 $1,986 Camping fees $235 1,577 $29 $69 Restaurants & bars $2,572 63,552 $1,019 $1,152 Amusements $1,067 21,148 $394 $662 Other vehicle expenses $112 811 $21 $49 Local transportation $32 690 $14 $16 Retail Trade $1,314 28,069 $533 $723 Wholesale Trade $230 2,090 $87 $153 Local Production of goods $336 965 $30 $45 Total Direct Effects $8,679 173,292 $3,348 $4,857 Secondary Effects $4,334 39,515 $1,167 $2,148 Total Effects $13,013 212,807 $4,516 $7,006 Note: Economic significance covers all $10.7 billion in spending of park visitors in the local region, including that of local visitors. Economic Impacts Excluding $1.1 billion dollars spent by local residents on park visits reduces the total spending to $9.6 billion (Table 2) for the impact analysis. Local visitors represent about 28% of all visits, but only 10% of all visitor spending. The total effects of visitor spending excluding locals is $11.6 billion in sales, $4.0 billion in personal income, $6.2 billion in value added and 190,000 jobs. The four economic sectors most directly affected are lodging, restaurants, retail trade and amusements. Visitor spending supports roughly 54,000 jobs in each of the hotel and restaurant sectors, over 23,000 jobs in retail trade, and 18,000 jobs in the amusements sector. 5

Table 4. Economic Impacts of National Park Visitor Spending on Local Economies, 2006 Sales $Millions $Millions Value Added $Millions Sector/Spending category Jobs Direct Effects Motel, hotel cabin or B&B $2,724 53,510 $1,190 $1,921 Camping fees $231 1,552 $28 $67 Restaurants & bars $2,181 54,093 $859 $964 Amusements $925 18,397 $339 $566 Other vehicle expenses $95 695 $18 $42 Local transportation $31 679 $14 $15 Retail Trade $1,092 23,418 $440 $593 Wholesale Trade $191 1,745 $72 $126 Local Production of goods $273 773 $24 $36 Total Direct Effects $7,744 154,861 $2,984 $4,329 Secondary Effects $3,842 35,068 $1,033 $1,904 Total Effects $11,586 189,929 $4,017 $6,233 Note: Economic impacts exclude spending of local visitors. Impacts of NPS payrolls National park units also impact local economies through their own spending, especially NPS payrolls 10. Payroll impacts were estimated for fiscal year (FY) 2006. In FY 2006 the National Park Service employed 24,284 people 11 with a total payroll of $1,163 million in wages and salaries and $302 million in payroll benefits (Table 5). The local economic impacts of park payrolls are $1.8 billion in personal income, $2.0 billion in value added and almost 36,000 jobs. Table 5. NPS Payroll Impacts on Local Economies, 2006 Payroll Payroll Salary ($Millions) Benefits ($Millions) Jobs Park units with visit data 790 209 17,813 Other units 373 92 6,471 Total 1,163 302 24,284 Local Impacts ($Millions) Value Added ($Millions) Jobs Park units with visit data 1,215 1,375 25,357 Other units 585 664 10,447 Total 1,800 2,039 35,804 10 Impacts of park purchases of supplies, services, and construction are not addressed as information on the proportion of these expenses accruing to local firms is not readily available. 11 The number of employees is estimated as an annual average for each park, so that seasonal positions are converted to annual equivalents. However, the job estimates include both full time and part time positions. 6

Impacts of park payrolls for each park unit were estimated by applying economic multipliers to wage and salary data to capture the induced effects of NPS employee spending on local economies. As with the MGM2 model, distinct multipliers were used for parks in rural areas, parks in or near small cities, and parks in larger metropolitan regions 12. The overall employment multiplier for NPS jobs is 1.5. For every two NPS jobs, another job is supported through the induced effects of employee spending in the local region. There are additional local economic effects from NPS purchases of goods and services from local suppliers and from construction activity. These impacts were not estimated. The visitor spending and payroll impacts may be combined, as park admission fees and most other visitor spending accruing to the National Park Service were omitted from the visitor spending figures to avoid double counting 13. Using the visitor spending impact estimates from Table 4, which exclude spending of local visitors, the combined impacts are $5.8 billion in personal income, $8.3 billion in value added, and 226,000 local jobs. Visitor spending accounts for 84% of the total jobs and 75% of the total value added (Table 6). Table 6. Combined Impacts - Visitor Spending and Payroll, 2006 Visitor Impact Measure Spending Impacts a NPS Payroll Impacts Combined Impacts Visitor Spending Share Direct Effects ($Millions) $2,984 $1,465 $4,448 67% Value Added ($Millions) $4,329 $1,465 $5,793 75% Jobs 154,861 23,978 178,839 87% Total Effects ($Millions) $4,017 $1,800 $5,817 69% Value Added ($Millions) $6,233 $2,039 $8,272 75% Jobs 189,929 35,804 225,733 84% a. Excludes spending by local visitors State-by-State Impact Estimates Economic impacts of individual parks can be aggregated to the state level with a few complications. While most parks fall within a single state, there are at least 20 park units with facilities in more than one state. For these parks, shares of visits were assigned to each state based on percentages provided by the NPS Public Use Statistics Office. It was assumed that spending and economic impacts are proportional to where the recreation visits were assigned. Estimates of recreation visits, spending and local economic impacts for each state and U.S. territory are given in Table A-4 in the Appendix. States receiving the greatest economic effects are California, Washington D.C., Arizona and North Carolina. 12 Multipliers for household spending were estimated in IMPLAN using the spending patterns of households with incomes of $50,000 -$75,000. 13 There will be some double counting of camping fees as payments to concessionaires could not be fully sorted out from payments to the NPS. 7

It should be noted that the state totals represent an accumulation of local impacts within roughly 50 miles of each park. The total economic effects on each state would be much larger if we estimated all spending of NPS visitors taking place within each state and used statewide multipliers instead of local ones to capture the secondary effects. As noted earlier, impacts reported here do not include long distance travel, airfares, or purchases made at home for items that may be used on trips to national parks. Trends 2001-2005 Recent trends in national park visits, spending and impacts are summarized in Table 7. Spending and economic impacts follow the trends in recreation visits. A small decline in visits in 2006 was offset by spending increases of 4.5% to yield an increase in overall visitor spending of 3.0%. For consistency with prior years, spending and impact figures in this table include local visitors. Impacts excluding local visitors are about 10% lower than when local visitors are included. Table 7. NPS System Recreation Visits, Spending and Impacts 2002-2006 a 2002 2003 2004 2005 2006 Recreation Visits (Millions) 277.3 266.1 276.9 272.6 e 272.3 e Party Days/Nights (Millions) b 107.6 103.2 107.3 105.6 103.4 Spending per party day $88 $91 $96 $99 $104 Total Spending ($Millions) $9,509 $9,403 $10,281 $10,423 $10,727 Direct Effects Direct c Sales ($Millions) $7,887 $7,741 $8,407 $8,387 $8,679 Direct jobs 191,381 183,767 193,478 186,807 173,292 Direct income ($Millions) $2,787 $2,737 $2,973 $2,992 $3,348 Direct value added ($Millions) $4,222 $4,148 $4,506 $4,535 $4,857 Total Local effects d Total sales ($ Millions) $11,459 $11,240 $12,206 $12,238 $13,013 Total jobs 240,806 231,102 243,398 234,803 212,807 Total income ($Millions) $4,080 $4,004 $4,349 $4,381 $4,516 Total value Added ($ Millions) $6,455 $6,336 $6,884 $6,943 $7,006 Note: All dollar figures are actual dollars, not adjusted for inflation. a. Spending and impact figures include visitors from the local area. b. Adjusts visits for park re-entries, party sizes, and length of stay in the region. Measured in days for day trips and nights for overnight trips. To the extent possible, only days/nights in the local area directly related to the park visit are counted. Average party sizes range from 2.0-3.0 across parks and visitor segments, systemwide the average party size is 2.6. c. Direct effects accrue to tourism-related businesses selling goods and services directly to park visitors. Jobs include full time and part time jobs. Seasonal jobs are adjusted to an annual basis. is personal income including wages and salaries, income of sole proprietors, and payroll benefits. Value added includes all personal income, rents and profits and indirect business taxes. d. Total local effects include direct, indirect and induced effects in the local regions around NPS units e. Beginning in 2005, visits to Kings Canyon and Sequoia National Parks were combined for the economic analysis and the combined visits for the two units were reduced to account for some double counting. Visit figures for these years are therefore slightly lower than those in the NPS Abstract. 8

Methods Spending and impacts were estimated using the Money Generation Model version 2 (MGM2). NPS public use statistics for calendar year 2006 provide estimates of the number of recreation visits and overnight stays at each park. For each park, recreation visits were allocated to the seven MGM2 segments 14, converted to party days/nights spent in the local area and then multiplied by per day spending averages for each segment. Spending and impact estimates for 2006 are made individually for each park unit and then summed to obtain systemwide totals. The system totals are therefore a sum of local impacts at each park, not an overall estimate of the impacts on the national economy 15. Spending averages for seven distinct visitor segments based on visitor surveys at selected national parks over the past six years were price adjusted to 2006 using Bureau of Labor Statistics (BLS) price indices. Spending averages cover all trip expenses within roughly 50 miles of the park. They therefore exclude most en route expenses on longer trips, as well as airfares, and purchases made at home in preparation for the trip, including costs of durable goods and equipment. Spending averages vary from park to park based on the type of park and the regional setting (low, medium or high spending area). For parks with recent visitor surveys, spending averages are estimated directly from the survey data with some adjustments for off-season use 16. Parks without recent visitor spending studies are assigned the MGM2 high, medium, or low spending profiles based on manager or researcher judgments. The segment mix is very important in estimating visitor spending as spending varies considerably across the MGM2 segments. Segment shares are estimated based on park overnight stay data and, where available, park visitor surveys. For park units that lack recent visitor surveys, estimates are made by generalizing from studies at similar parks or based on manager or researcher judgment. For parks with VSP studies (Visitor Services Project) over the past seven years, spending averages are estimated from the survey data at each park 17. Averages estimated 14 Visits are classified as local day trips, non-local day trips, and overnight trips staying in campgrounds or hotels, lodges, cabins and B&B s. For parks with lodging facilities within the park, visitors staying in park lodges, campgrounds or backcountry sites are distinguished from those staying outside the park in motels or non-nps campgrounds. Visitors staying with friends or relatives, in owned seasonal homes, or passing through without a local overnight stay are generally treated as day trips. 15 Applying park visitor spending to a national model/set of multipliers would capture 98% of visitor spending as direct sales (instead of the 80% that accrues to firms in the local regions around each park) and would also yield significantly larger secondary effects. National sales multipliers for tourism spending are about 2.5, while the average sales multiplier for local regions around parks is only 1.5. 16 Most park surveys are conducted during the peak season, so estimates of segment shares and spending must be adjusted for seasonal differences. 17 Detailed impact reports for parks that have included economic questions in their VSP studies are available at the MGM2 (http://web4.canr.msu.edu/mgm2/) or NPS social science websites (http://www.nature.nps.gov/socialscience/products.cfm#mgm2reports). 9

in the surveys were price adjusted to 2006 using BLS price indices for each spending category. Sampling errors for the spending averages in VSP studies are generally 5-10% overall and can be as high as 20% for individual visitor segments. The observed spending patterns in park visitor studies are then used to estimate spending averages for other parks that lack visitor spending surveys. This procedure will not capture some spending variations attributable to unique characteristics of a given park or gateway region, for example, the wider use of public transportation at Alaska parks or extra expenses for special commercial attractions in or around some parks, such as rafting trips, flightseeing and other tours. When visitor studies are conducted at individual parks, these unique situations are taken into account. For example, river runners were treated as a distinct segment at Grand Canyon National Park (Stynes and Sun 2005). Multipliers for local regions around national parks 18 were applied to the spending totals to translate spending into jobs, income and value added and also to estimate secondary effects. All MGM2 multipliers were re-estimated for 2006 using 2001 IMPLAN data, based on the North American Industrial Classification System (NAICS). Previous MGM2 estimates employed multipliers from 1996 IMPLAN models with economic sectors based on SIC codes. The updating of multipliers reduces job estimates by about 10% compared to previous estimates, due to declining job to sales ratios in many of the key tourism-related sectors. For most parks, we use generic multipliers built into the MGM2 model (Stynes and Sun 2000) 19. The appropriate generic multipliers for each park are selected based on the population of the surrounding region. Generic multipliers were estimated as averages across over 100 distinct IMPLAN models for each type of region. The maximum observed absolute deviations between the IMPLAN multipliers for individual regions and the corresponding generic multiplier for that region are generally 10% or less and on average the differences are less than 5% (Chang 2001). The larger deviations, typically in job to sales ratios, can be due to errors in the underlying IMPLAN data. In this respect, the generic multipliers average out some errors in IMPLAN data for individual regions. The generic approach to multipliers works well for tourism-related applications because the vast majority of visitor spending accrues to service industries. These sectors are quite labor intensive and the other inputs to production are primarily utilities and services that tend to exist in an area in direct proportion to population size. Hence secondary effects are predicted fairly well based on the local population size. Note that the IMPLAN estimates of the ratios of income and value added to sales for each sector are essentially constant across regions since IMPLAN uses a national average production function for each sector. Only the IMPLAN estimates of job to sales 18 Multipliers are developed using the IMPLAN input-output modeling system (MIG, Inc.). 19 For some parks we have used custom IMPLAN models estimated for the county or counties around the park to derive the multipliers. In all of these cases, the impact results with the custom multipliers were not significantly different than with the appropriate generics. 10

ratios and secondary effects vary significantly between regions and these variations are captured quite well for service and retail sectors by the population of the region. With the exception of parks with new visitor surveys in 2004 or 2005, no changes were made in party sizes, lengths of stay or re-entry factors between 2005 and 2006. Local economic ratios and multipliers were also assumed constant, except for job to sales ratios, which were adjusted to 2006 based on the consumer price index. MGM2 model parameters for individual parks are adjusted over time as new park visitor studies are conducted or other relevant information becomes available. Impacts of park payrolls were estimated for each park by applying local area multipliers to NPS wage and salary figures for FY 2006. Multipliers capture the induced effects of park employee spending by recirculating their income as household spending within the local economy. Payroll benefits were not re-circulated in estimating secondary effects of park employee spending, but the direct payroll benefits are included in total value added. Four sets of household spending multipliers were estimated to capture variations in impacts across regions based on population size 20. Local impacts of park purchases of supplies and services or construction activities were not included in the analysis. The number of employees for each park was estimated by totaling the number of distinct social security numbers in each pay period and dividing by the number of pay periods. The figure is therefore an annual average. Four seasonal jobs for three months count as one job. No distinction is made between part time and full time employees. Jobs, salary and payroll benefits are assigned to the park where the employee s time was charged, which may differ from their duty station. Where possible, the unit org codes were used to separate out payroll data for parks that are administered under a different park alpha code 21. Spending and impact totals for states were developed from the 2005 estimates by simply summing the results for all units in a given state using the mailing address for the park to identify the state. For 2006, we identified 20 parks with facilities in more than one state. For these parks, visitors and spending were allocated to individual states based on shares provided by the NPS Public Use Statistics Office. For example, visits to Great Smoky Mountains NP were split 44% to North Carolina and 56% to Tennessee. It should be noted that these allocations may not fully account for where the spending and impacts occur. There are also many other parks with facilities in a single state, but located within 50 miles of a state border. A portion of the spending and impacts for these parks may 20 IMPLAN s spending patterns for households averaging $50,000- $75,000 were used to estimate the multipliers. 21 Each park has a four letter alpha code. Budgets, however, are itemized by organization (org) codes. A given park may receive funds under several distinct org codes. Also, some smaller park units are administered under a different park that serves as the home org. For example Eisenhower NHS is administered under Gettysburg NMP. 11

accrue to nearby states. For example, the local region for Saint-Gaudens NHS included counties in both Vermont and New Hampshire (Stynes, 2006a), but all impacts in this report are assigned to New Hampshire, since the visitor surveys do not identify exactly where spending may have occurred within the local region. Errors and Limitations The accuracy of the spending and impact estimates rests largely on the input data, namely (1) public use recreation visit and overnight stay data, (2) party size, length of stay and park re-entry conversion factors, (3) visitor segment shares, (4) spending averages, and (5) local area multipliers. Public use data provide reasonably accurate estimates of visitor entries for most parks. Some visitors may be missed by the counting procedures, while others may be counted multiple times when they re-enter a park more than once on a single trip. Accurate estimates of park re-entries, party sizes and lengths of stay in the area are needed to convert park entries to the number of visitor or party days in the region. Visitors staying overnight outside the park pose significant problems as they tend to be the greatest spenders and may enter the park several times during their stay. Similarly, visitors staying inside the park may enter and leave several times during their stay and be counted each time as a distinct visit. Re-entry factors adjust for these problems to the extent possible. For multi-purpose trips, it is difficult to determine what portion of the spending should be attributed to the park visit. This is especially a problem for historic sites and parks in urban areas or parks in multiple-attraction destinations. For parks with visitor surveys, the proportion of days and spending counted was decided based on stated trip purposes and the importance of the park in generating the trip to the region. Parkways and urban parks pose special difficulties for economic impact analyses. These units have some of the highest number of visits while posing the most difficult problems for estimating visits, spending and impacts. The majority of visits to these types of units were assumed to be local or non-local day trips and only one night of spending was counted for overnight trips. Due to the high numbers of visits at these units, small changes in assumed spending averages or segment mixes can swing the spending estimates by substantial amounts. Clusters of parks within a single 50 mile area pose additional difficulties. For example, the many monuments and parks in the Washington D.C. area each count visitors separately. To avoid double counting of spending across many national capital parks, we must know how many times a visitor has been counted at park units during a trip to the Washington D.C. area. For parks in the national capital region, we currently assume an average of 1.7 park visits are counted for local day trips, 3.4 visits for non-local day trips and 5.1 park visits on overnight trips. Similar difficulties exist for clusters of parks in Boston, New York, and San Francisco. 12

Double counting of visits at Sequoia and Kings Canyon National Parks was sorted out in 2002 based on vehicle counts at each entrance (Stynes and Sun 2003). For parks that are at least 50 miles apart, the MGM2 procedure assigns spending based on the number of days/nights spent in the local area. It therefore avoids double counting of spending for visitors on extended trips visiting several parks that are at least 50 miles apart, a common pattern at many western parks. Suggestions for Further Research Refinements to the impact estimates should focus first on the visitation data, as the number of visits drives the changes in spending and impact estimates over time. Analysts using NPS recreation visit data frequently interpret estimates of recreation visits as if these represent distinct trips rather than simply entries to the park. This confusion has resulted in many inflated estimates of visitor spending when trip spending averages are applied to recreation visits without adjustments for re-entries. The extent of potential double counting of visitors (due to re-entries to parks and parks in close proximity to one another) is not well known for many parks. It would be useful to more fully sort out the double counting problem at each park and to report both park entries and the number of distinct person trips. In estimating spending it is quite important to be able to divide visitors into distinct segments with different spending patterns. Day visitors and locals spend much less than visitors on overnight trips. Spending of overnight visitors varies across lodging types. For parks lacking recent visitor surveys, the visitor segment mix is not well known. The mix of visitors may also change over time due to changes in populations surrounding the park and park use patterns. While park overnight stay data provides good estimates of overnight visitors who stay in the park, all other visitors are generally treated as day visitors (to the park), even though many are staying overnight in gateway communities. Visitors staying overnight outside the park usually have the greatest economic impacts on the local economy. It is therefore important to distinguish between local residents, day trips from beyond 50 miles, and overnight stays in area motels, campgrounds or private homes. These segment shares can be estimated in visitor surveys. We also recommend that parks, in cooperation with regional tourist organizations, track lodging capacities and occupancy rates in gateway communities in order to better understand the mix of visitor accommodations inside and outside the park. Deciding what proportion of trips and spending to attribute to a park visit is a difficult issue, particularly for smaller parks and historic sites that may not be the primary reason for many trips, but instead something for tourists to do while in an area. Attributing spending to the park visit requires more complete information about visitors including their trip purposes and other activities in the area (Tyrrell and Johnston 2001). 13

This information has been gathered in recent VSP studies, but it is not available for most parks. For visitors on multi-purpose trips, the share of trip expenses to be attributed to the park visit is inherently somewhat arbitrary. Theoretically, we would like to know which trips would not have been made in the absence of the park and/or what additional spending resulted from the park visit. These are sometimes difficult questions for visitors to answer. The VSP program of conducting visitor surveys at a dozen or more parks each year should be continued. In addition to providing basic information about visitor characteristics, attitudes and park use patterns, VSP data supports the analysis of economic impacts of park visitors on local regions. Visitor spending averages used in the MGM2 model are refined each year as new visitor surveys are completed. The great diversity in NPS units, visitors, and spending opportunities poses difficulties in generalizing from one park to another. While price indices can be used to update spending averages over time, they may not fully account for possible structural changes in trip characteristics and spending patterns. VSP studies could be supplemented with other studies of particular visitor segments with high or unique spending patterns. These segments might be tackled by sampling at several parks during a single year. Examples include national park campers and visitors in lodges, backcountry visitors, river runners, visitors on bus tours, and school groups, particularly at historic sites and nature centers. These types of visitors are often missed in VSP studies or the samples are too small to yield reliable spending averages. The MGM2 generic multipliers were updated this year using 2001 IMPLAN data sets. The general practice is to develop custom IMPLAN models when estimating impacts in conjunction with a VSP survey, and to employ MGM2 generic multipliers for other parks. Unique multipliers for each park could be developed using the IMPLAN system. This would require the identification of counties to be included in the local region for each park. The problems associated with sorting out impacts for parks that involve more than one state are likely best addressed on a case by case basis. Perhaps the best candidates for such studies would be parks in the Washington DC area, and the Blue Ridge and Natchez Trace Parkways. A regional analysis makes more sense than estimating impacts park by park in the DC area. For parkways and other parks involving multiple states, the specific locations of park entrances and commercial development dictate where the economic impacts will occur. Sorting out exactly where the impacts occur requires more detailed spatial analysis of visitor use and spending patterns at these parks. Such studies are best conducted for individual parks, where the additional data collection costs can be justified. It is always useful to be able to ground spending and impact estimates in hard data and to attempt to triangulate across multiple sources. For parks with significant concession operations, park concessionaire data could be more fully utilized to validate 14

estimates of spending inside the park. Some parks support significant commercial operations around the park, such as whitewater rafting, flightseeing, horseback operations, and guided tours. These are not fully covered in our spending estimates, except for selected parks with recent visitor surveys. Estimates of sales, income and jobs associated with national park visitors can also be compared with overall economic figures for a given area or with tourism impact estimates. However, local tourism estimates are sometimes exaggerated and one must be careful in comparing studies that may involve distinct methods and coverage. Tourism figures may include airfares and other items not covered in the MGM2 park impact figures. Impacts may also be reported in different units (e.g., jobs vs full time equivalents) or covering larger or smaller geographic areas. Economic impact analyses rest considerably on the definition of the impact region. Cooperative studies with local tourism and regional development interests are recommended to better understand the role of each park in the area economy, and especially the park s role in attracting and serving visitors to an area. Visitor studies should cover information sources and patterns of use both within and outside the park, and especially the extent and use of lodging facilities near the park. References Chang, Wen-Huei. 2001. Variations in multipliers and related economic ratios for recreation and tourism impact analysis. Ph.D. Dissertation, East Lansing, MI : Michigan State University. Minnesota IMPLAN Group Inc. 1999. IMPLAN Pro Version 2, Social Accounting and Impact Analysis Software. Stillwater, MN. Stynes, D.J., Propst, D.B., Chang, W.H., and Sun, Y. 2000. Estimating regional economic impacts of park visitor spending: Money Generation Model Version 2 (MGM2). East Lansing, MI: Department of Park, Recreation and Tourism Resources, Michigan State University. Stynes, Daniel J. and Sun, Ya-Yen. 2003. Impacts of Visitor Spending on the Local Economy; Sequoia and Kings Canyon National Parks, 2002. East Lansing, MI: Department of Park, Recreation and Tourism Resources, Michigan State University. Stynes, Daniel J. and Sun, Ya-Yen. 2003. Economic Impacts of National Park Visitor Spending on the Local Economy; Systemwide estimates for 2001. Final Report to National Park Service. East Lansing MI: Department of Park, Recreation, and Tourism Resources, Michigan State University. 15

Stynes, Daniel J. and Sun, Ya-Yen. 2005. Economic Impacts of Grand Canyon National Park Visitor Spending on the Local Economy, 2003. East Lansing, MI: Department of Park, Recreation and Tourism Resources, Michigan State University. Stynes, Daniel J. 2005. National Park Visitor Spending and Local Economic Impacts, 2003. Report to National Park Service. East Lansing MI: Department of Community, Agriculture, Recreation, and Resource Studies. Michigan State University. Stynes, Daniel J. 2006. National Park Visitor Spending and Payroll Impacts, 2005. Report to National Park Service. East Lansing MI: Department of Community, Agriculture, Recreation, and Resource Studies. Michigan State University. Stynes, Daniel J. 2006a. Impacts of Visitor Spending on the Local Economy: Saint- Gaudens National Historic Site, 2004. East Lansing MI: Department of Community, Agriculture, Recreation, and Resource Studies. Michigan State University. Tyrrell, Timothy J. and Johnston, Robert J. 2001. A Framework for Assessing Direct Economic Impacts of Tourist Events: Distinguishing Origins, Destinations, and Causes of Expenditures. Journal of Travel Research (40): 94-100. 16

Appendix Visitor Spending and Payroll Impacts by Park, 2006 Table Page Table A-1. Spending and Local Economic Impacts by Park, CY 2006 18 Table A-2. Payroll Impacts on Local Economies by Park, FY 2006 28 Table A-3. Payroll Impacts on Local Economies, Administrative Units and Parks without Visit Counts, 2006 37 Table A-4. Impacts of NPS Visitor Spending and Payroll on Local Economies by State, 2006 40 17

Table A-1. Spending and Local Economic Impacts by Park, CY 2006 Public Use Data Visitor Spending 2006 Impacts of Non-Local Visitor Spending 2006 Recreation Visits 2006 OVN stays All Visitors Non-Local Visitors Jobs Value Added Abraham Lincoln Birthplace NHS 200,054 0 $ 6,954 $ 6,476 129 $ 2,248 $ 3,476 Acadia NP 2,083,588 127,157 132,340 129,476 2,604 51,707 80,029 Adams NHS 225,318 0 14,546 13,545 254 6,297 9,793 Agate Fossil Beds NM 13,521 0 470 438 9 152 235 Alibates Flint Quarries NM 1,882 0 93 87 2 35 54 Allegheny Portage Railroad NHS 121,009 0 6,009 5,596 113 2,235 3,459 Amistad NRA 1,599,271 35,312 45,405 39,465 787 13,702 21,186 Andersonville NHS 132,153 0 4,594 4,278 85 1,485 2,296 Andrew Johnson NHS 50,701 0 2,518 2,345 47 936 1,449 Antietam NB 282,676 3,730 13,510 12,127 244 4,843 7,496 *Apostle Islands NL 189,051 25,675 20,454 16,185 351 6,928 9,807 Appomattox Court House NHP 145,804 0 7,241 6,742 136 2,693 4,168 *Arches NP 833,049 51,855 80,439 80,439 1,949 30,318 47,839 Arkansas Post NMem 36,665 0 1,275 1,187 24 412 637 Arlington House, Robert E. Lee Mem 509,522 0 32,894 30,631 575 14,240 22,146 Assateague Island NS 1,932,817 95,576 137,071 130,325 2,621 52,046 80,554 Aztec Ruins NM 40,779 0 1,299 1,252 25 500 774 *Badlands NP 840,118 34,903 18,149 18,149 390 6,130 9,842 Bandelier NM 243,765 12,054 10,990 10,545 212 4,211 6,518 Bent's Old Fort NHS 26,483 0 921 857 17 298 460 Bering Land Bridge Npres 1,265 432 61 58 1 20 31 Big Bend NP 298,717 164,029 12,465 11,882 237 4,125 6,379 Big Cypress Npres 825,857 27,942 76,126 72,343 1,359 33,632 52,304 Big Hole NB 55,049 0 1,914 1,782 36 619 957 Big South Fork NRRA 622,807 68,974 21,904 18,790 375 6,524 10,087 Big Thicket NPres 91,126 1,125 6,466 6,142 124 2,453 3,796 Bighorn Canyon NRA 177,414 13,121 5,117 4,475 89 1,554 2,402 *Biscayne NP 608,836 8,000 37,237 36,830 651 15,562 24,659 Black Canyon of the Gunnison NP 160,450 12,863 7,954 7,568 151 2,627 4,063 Blue Ridge Parkway 18,953,478 142,472 348,151 314,610 6,328 125,641 194,461 Bluestone NSR 46,093 0 1,857 1,610 32 643 995 Booker T. Washington NM 18,339 0 911 848 17 339 524 Boston African American NHS 255,060 0 16,466 15,333 288 7,128 11,086 Boston NHP 1,944,386 0 64,440 62,010 1,165 28,828 44,833 Brown V. Board of Education NHS 20,926 0 1,039 968 18 450 700 Bryce Canyon NP 890,676 128,125 45,645 43,572 869 15,128 23,391 Buck Island Reef NM 47,456 3,920 3,362 3,199 64 1,111 1,718 Buffalo National River 1,068,090 100,235 30,980 27,134 541 9,421 14,567 18

Table A-1. Spending and Local Economic Impacts by Park, CY 2006 Public Use Data Visitor Spending 2006 Impacts of Non-Local Visitor Spending 2006 Recreation Visits 2006 OVN stays All Visitors Non-Local Visitors Jobs Value Added Cabrillo NM 804,826 0 51,958 48,383 909 22,493 34,981 Canaveral NS 1,005,402 2,883 71,391 67,801 1,364 27,077 41,908 Cane River Creole NHP 34,453 0 1,711 1,593 32 553 855 Canyon de Chelly NM 826,635 56,135 39,691 36,960 743 14,760 22,845 Canyonlands NP 392,537 87,422 19,252 18,353 366 6,372 9,852 Cape Cod NS 4,487,716 17,720 153,381 114,037 2,274 39,592 61,219 Cape Hatteras NS 2,125,005 83,773 68,683 64,642 1,289 22,443 34,702 Cape Krusenstern NM 2,598 505 84 79 2 27 42 Cape Lookout NS 803,155 35,518 40,744 38,775 773 13,462 20,816 Capitol Reef NP 511,511 32,572 25,381 24,140 481 8,381 12,959 *Capulin Volcano NM 49,823 0 1,293 1,272 27 418 673 Carl Sandburg Home NHS 28,799 0 1,430 1,332 27 532 823 Carlsbad Caverns NP 407,367 95 19,639 18,989 382 7,583 11,737 Casa Grande Ruins NM 88,295 0 2,695 2,540 51 882 1,363 Castillo de San Marcos NM 630,903 0 40,730 37,928 712 17,632 27,422 Castle Clinton NM 3,415,397 0 87,515 78,473 1,474 36,482 56,736 Catoctin Mountain Park 526,898 37,619 25,270 23,531 473 9,397 14,545 Cedar Breaks NM 488,376 2,038 16,943 15,777 315 5,478 8,470 Central High School 35,264 0 1,751 1,631 33 651 1,008 Chaco Culture NHP 37,923 15,480 1,247 1,221 25 487 755 Chamizal NMem 221,048 0 14,270 13,289 250 6,178 9,608 Channel Islands NP 375,256 164,404 34,130 32,741 615 15,221 23,672 Charles Pinckney NHS 36,556 0 1,815 1,690 34 675 1,045 Chattahoochee River NRA 2,842,670 0 78,252 52,575 988 24,442 38,012 *Chesapeake & Ohio Canal NHP 3,039,178 4,276 36,410 23,489 513 11,504 17,867 Chickamauga & Chattanooga NMP 919,892 1,806 45,638 42,499 855 16,972 26,269 Chickasaw NRA 1,343,793 72,754 38,548 33,636 671 11,678 18,057 Chiricahua NM 61,579 9,792 2,825 2,630 53 1,050 1,626 Christiansted NHS 100,868 0 3,506 3,265 65 1,134 1,753 City of Rocks NRES 77,131 0 5,478 5,202 105 2,078 3,216 Clara Barton NHS 12,495 0 807 751 14 349 543 *Colonial NHP 3,344,018 0 47,325 6,107 142 2,948 4,612 Colorado NM 332,654 12,954 16,212 15,096 304 6,029 9,331 Congaree Swamp NM 134,045 2,225 6,609 6,154 124 2,458 3,804 Coronado Nmem 70,063 0 2,436 2,268 45 787 1,218 Cowpens NB 143,664 204 7,129 6,639 134 2,651 4,104 *Crater Lake NP 388,972 61,893 27,988 27,187 641 9,850 15,842 *Craters of the Moon NM 176,998 11,860 4,847 4,303 68 1,683 2,404 Cumberland Gap NHP 936,929 15,790 46,165 42,990 865 17,168 26,572 19

Table A-1. Spending and Local Economic Impacts by Park, CY 2006 Public Use Data Visitor Spending 2006 Impacts of Non-Local Visitor Spending 2006 Recreation Visits 2006 OVN stays All Visitors Non-Local Visitors Jobs Value Added Cumberland Island NS 44,025 13,005 3,086 2,949 59 1,178 1,823 Curecanti NRA 936,380 50,952 38,375 33,486 673 13,373 20,698 Cuyahoga Valley NP 2,468,816 4,472 50,110 36,134 679 16,799 26,125 *Dayton Aviation Heritage NHP 51,771 0 2,525 1,399 33 702 1,039 De Soto Nmem 245,503 0 15,849 14,759 277 6,861 10,671 Death Valley NP 744,440 212,627 38,081 36,476 727 12,664 19,582 Delaware Water Gap NRA 5,254,216 110,246 131,738 115,323 2,319 46,055 71,282 Denali NP & Pres 415,935 99,757 29,241 27,910 561 11,146 17,251 Devils Postpile NM 105,303 4,027 3,593 3,346 67 1,162 1,796 Devils Tower NM 335,764 8,918 11,523 10,730 214 3,725 5,760 Dinosaur NM 278,473 47,097 9,037 8,416 168 2,922 4,518 Dry Tortugas NP 64,122 14,840 5,881 5,616 105 2,611 4,060 Edgar Allan Poe NHS 12,409 0 801 746 14 347 539 Edison NHS 8,753 0 565 526 10 245 380 *Effigy Mounds NM 90,199 0 4,902 1,875 38 702 1,044 *Eisenhower NHS 70,243 0 4,181 4,151 106 1,604 2,572 El Malpais NM 107,792 520 4,052 3,880 77 1,347 2,083 El Morro NM 52,297 2,753 1,880 1,796 36 624 964 Eleanor Roosevelt NHS 14,493 0 504 469 9 163 252 Eugene O'Neill NHS 3,372 0 218 203 4 94 147 Everglades NP 954,022 36,241 50,351 48,577 912 22,583 35,121 Federal Hall NMem 12,800 0 826 769 14 358 556 Fire Island NS 636,030 39,677 33,621 27,919 562 11,149 17,257 First Ladies NHS 11,219 0 724 674 14 269 417 Florissant Fossil Beds NM 56,094 0 2,786 2,594 52 1,036 1,603 Ford's Theatre NHS 857,600 0 24,783 22,543 423 10,480 16,299 Fort Bowie NHS 10,679 0 530 494 10 197 305 Fort Caroline NMem 224,114 0 14,468 13,473 253 6,264 9,741 Fort Davis NHS 49,091 0 1,706 1,589 32 552 853 Fort Donelson NB 213,521 1,502 7,397 6,888 137 2,392 3,698 Fort Frederica NM 316,611 0 15,723 14,641 294 5,847 9,050 Fort Laramie NHS 40,651 0 1,413 1,316 26 457 706 Fort Larned NHS 31,512 0 1,095 1,020 20 354 548 Fort Matanzas NM 922,315 0 59,542 55,446 1,041 25,777 40,087 Fort McHenry NM & HS 622,419 0 40,182 37,418 703 17,395 27,053 Fort Necessity NB 221,598 149 7,350 6,339 126 2,201 3,403 Fort Point NHS 1,613,853 0 104,186 97,019 1,822 45,104 70,144 Fort Pulaski NM 333,378 19 16,555 15,416 310 6,157 9,529 Fort Raleigh NHS 299,432 0 10,409 9,693 193 3,365 5,203 20